Fundamentals of Artificial Intelligence and Machine Learning

This guide provides a comprehensive understanding of the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML), exploring their definitions, core concepts, and applications. It begins by defining AI as the simulation of human intelligence in machines, categorizing it into Narrow AI and General AI. Narrow AI is designed for specific tasks, while General AI aims to replicate human cognitive abilities. The document then details Machine Learning as a subset of AI that develops algorithms enabling computers to learn from data. It outlines key components of ML, including supervised, unsupervised, and reinforcement learning, with examples of their applications. Furthermore, the guide discusses core concepts such as neural networks, data and features, training and testing processes, and various algorithms used in AI and ML. Finally, it highlights applications of these technologies in sectors like healthcare and finance, illustrating how they enhance decision-making and operational efficiencies across industries.